Abstract: In order to improve the accuracy and efficiency of leakage detection for long-distance pipeline, the modified fuzzy C-means algorithm is applied. Particle swarm optimization algorithm is introduced to optimize the troditional fuzzy C-means algorithm, which is used to represent the gradient descent so as to improve the efficiency and accuracy of fuzzy C-means algorithm. Then the proposed fuzzy C-means algorithm is used to analyze the same group of pipeline leakage experimental data compared with troditional fuzzy C-means algorithm and 3-layer BP (Back Propagation) neural network. The result proves that the proposed fuzzy C-means algorithm has a better property than the other two algorithms, so it is feasible to apply the PSO-based Fuzzy C-Means model in pipeline leakage detection.

Key words: particle swarm optimization, fuzzy c-means, long-distance pipeline leakage detection